Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6873419 | Future Generation Computer Systems | 2018 | 12 Pages |
Abstract
To address the high-performance challenges of data transfer in the big data era, we are developing and implementing mdtmFTP: a high-performance data transfer tool for big data. mdtmFTP has four salient features. First, it adopts an I/O centric architecture to execute data transfer tasks. Second, it more efficiently utilizes the underlying multicore platform through optimized thread scheduling. Third, it implements a large virtual file mechanism to address the lots-of-small-files (LOSF) problem. Finally, mdtmFTP integrates multiple optimization mechanisms, including-zero copy, asynchronous I/O, pipelining, batch processing, and pre-allocated buffer pools-to enhance performance. mdtmFTP has been extensively tested and evaluated within the ESNET 100G testbed. Evaluations show that mdtmFTP can achieve higher performance than existing data transfer tools, such as GridFTP, FDT, and BBCP.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Liang Zhang, Wenji Wu, Phil DeMar, Eric Pouyoul,